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<p>基于图割（Graph Cut）的点云分割方法，适用于前景背景分离任务。</p>
</blockquote>
<hr>
<h2 id="核心原理"><a href="#核心原理" class="headerlink" title="核心原理"></a>核心原理</h2><p><code>MinCutSegmentation</code> 是一种基于 <strong>图割（Graph Cut）</strong> 的分割方法，其基本思想是：</p>
<ul>
<li>将点云建模为一个图（Graph）：<ul>
<li>每个点是一个节点。</li>
<li>点之间通过边连接，边权由空间距离和相似性决定。</li>
</ul>
</li>
<li>引入两个虚拟节点：<ul>
<li><strong>Source（源点）</strong>：代表前景。</li>
<li><strong>Sink（汇点）</strong>：代表背景。</li>
</ul>
</li>
<li>利用最小割算法将图分为两部分，使得割的总权重最小，即能量函数最小化。</li>
</ul>
<p>该方法特别适合 <strong>已知前景种子点</strong> 的场景，能实现高精度的物体提取。</p>
<hr>
<h2 id="关键参数说明"><a href="#关键参数说明" class="headerlink" title="关键参数说明"></a>关键参数说明</h2><table>
<thead>
<tr>
<th>参数</th>
<th>方法</th>
<th>作用</th>
<th>推荐值</th>
</tr>
</thead>
<tbody><tr>
<td><code>setSigma()</code></td>
<td><code>seg.setSigma(Sigma)</code></td>
<td>控制平滑项权重，影响相邻点是否被分到同一类</td>
<td>0.01 ~ 1.0</td>
</tr>
<tr>
<td><code>setRadius()</code></td>
<td><code>seg.setRadius(Radius)</code></td>
<td>距离种子点超过此半径的点更可能被划为背景</td>
<td>根据物体尺寸设置</td>
</tr>
<tr>
<td><code>setNumberOfNeighbours()</code></td>
<td><code>seg.setNumberOfNeighbours(14)</code></td>
<td>每个点连接的邻居数，影响图的稠密度</td>
<td>8 ~ 20</td>
</tr>
<tr>
<td><code>setSourceWeight()</code></td>
<td><code>seg.setSourceWeight(0.5)</code></td>
<td>前景点与源点连接的权重，越大越倾向保留为前景</td>
<td>0.1 ~ 1.0</td>
</tr>
<tr>
<td><code>setForegroundPoints()</code></td>
<td><code>seg.setForegroundPoints(...)</code></td>
<td>提供前景种子点，引导分割方向</td>
<td>至少一个有效点</td>
</tr>
</tbody></table>
<hr>
<h2 id="命令行使用方式"><a href="#命令行使用方式" class="headerlink" title="命令行使用方式"></a>命令行使用方式</h2><p>支持通过命令行传参，灵活调整参数：</p>
<figure class="highlight bash"><table><tr><td class="gutter"><pre><span class="line">1</span><br></pre></td><td class="code"><pre><span class="line">./mincut_segmentation input.pcd -bc 1 -<span class="built_in">fc</span> 1.5 -nc 0.2 -cx 0 -cy 0 -cz 1 -s 0.2 -r 1.0 -non 10 -sw 0.8</span><br></pre></td></tr></table></figure>

<table>
<thead>
<tr>
<th>参数</th>
<th>含义</th>
</tr>
</thead>
<tbody><tr>
<td><code>-bc 1</code></td>
<td>开启直通滤波（Z轴裁剪）</td>
</tr>
<tr>
<td><code>-fc 1.5</code></td>
<td>Z轴最大值（远裁剪）</td>
</tr>
<tr>
<td><code>-nc 0.2</code></td>
<td>Z轴最小值（近裁剪）</td>
</tr>
<tr>
<td><code>-cx 0</code></td>
<td>前景种子点 X 坐标</td>
</tr>
<tr>
<td><code>-cy 0</code></td>
<td>前景种子点 Y 坐标</td>
</tr>
<tr>
<td><code>-cz 1</code></td>
<td>前景种子点 Z 坐标</td>
</tr>
<tr>
<td><code>-s 0.2</code></td>
<td>Sigma 值</td>
</tr>
<tr>
<td><code>-r 1.0</code></td>
<td>背景惩罚半径</td>
</tr>
<tr>
<td><code>-non 10</code></td>
<td>邻居数量</td>
</tr>
<tr>
<td><code>-sw 0.8</code></td>
<td>Source 权重</td>
</tr>
</tbody></table>
<hr>
<h2 id="可视化技巧"><a href="#可视化技巧" class="headerlink" title="可视化技巧"></a>可视化技巧</h2><ul>
<li>✅ <code>getColoredCloud()</code>：自动生成 RGB 着色点云：<ul>
<li><strong>红色</strong>：前景（目标物体）</li>
<li><strong>白色</strong>：背景</li>
</ul>
</li>
<li>✅ <code>addSphere()</code>：可视化背景惩罚范围，帮助理解 <code>Radius</code> 的影响。</li>
<li>✅ <code>setShapeRenderingProperties(OPACITY)</code>：设置透明度，避免遮挡点云。</li>
</ul>
<p>示例代码：</p>
<figure class="highlight cpp"><table><tr><td class="gutter"><pre><span class="line">1</span><br><span class="line">2</span><br></pre></td><td class="code"><pre><span class="line">viewer.<span class="built_in">addSphere</span>(point, Radius, <span class="number">122</span>, <span class="number">122</span>, <span class="number">0</span>, <span class="string">&quot;sphere&quot;</span>);</span><br><span class="line">viewer.<span class="built_in">setShapeRenderingProperties</span>(pcl::visualization::PCL_VISUALIZER_OPACITY, <span class="number">0.2</span>, <span class="string">&quot;sphere&quot;</span>);</span><br></pre></td></tr></table></figure>

<hr>
<h2 id="常见问题与优化建议"><a href="#常见问题与优化建议" class="headerlink" title="常见问题与优化建议"></a>常见问题与优化建议</h2><table>
<thead>
<tr>
<th>问题</th>
<th>可能原因</th>
<th>解决方案</th>
</tr>
</thead>
<tbody><tr>
<td>分割失败或结果混乱</td>
<td>种子点不在目标物体上</td>
<td>确保 <code>-cx</code>, <code>-cy</code>, <code>-cz</code> 正确</td>
</tr>
<tr>
<td>运行太慢</td>
<td>点云太大或邻居数过多</td>
<td>先下采样（voxel grid）或减少 <code>-non</code></td>
</tr>
<tr>
<td>前景太小或太大</td>
<td><code>SourceWeight</code> 或 <code>Radius</code> 不合适</td>
<td>调整 <code>-sw</code> 和 <code>-r</code></td>
</tr>
<tr>
<td>点云无法加载</td>
<td>文件路径错误或格式不支持</td>
<td>检查 <code>.pcd</code> 文件是否包含 <code>x,y,z</code> 字段</td>
</tr>
<tr>
<td>编译报错</td>
<td>PCL 库未正确安装或链接</td>
<td>确保安装 <code>libpcl-dev</code> 并正确配置 CMake</td>
</tr>
</tbody></table>
<hr>
<h2 id="典型应用场景"><a href="#典型应用场景" class="headerlink" title="典型应用场景"></a>典型应用场景</h2><ul>
<li>✅ 人体或车辆分割（自动驾驶）</li>
<li>✅ 工业零件提取（机器人抓取）</li>
<li>✅ 手势识别中的手部分割</li>
<li>✅ 结合 RANSAC 去除地面后，提取障碍物</li>
<li>✅ 半自动图像标注辅助工具</li>
</ul>
<hr>
<h2 id="代码实现"><a href="#代码实现" class="headerlink" title="代码实现"></a>代码实现</h2><figure class="highlight cpp"><table><tr><td class="gutter"><pre><span class="line">1</span><br><span class="line">2</span><br><span class="line">3</span><br><span class="line">4</span><br><span class="line">5</span><br><span class="line">6</span><br><span class="line">7</span><br><span class="line">8</span><br><span class="line">9</span><br><span class="line">10</span><br><span class="line">11</span><br><span class="line">12</span><br><span class="line">13</span><br><span class="line">14</span><br><span class="line">15</span><br><span class="line">16</span><br><span class="line">17</span><br><span class="line">18</span><br><span class="line">19</span><br><span class="line">20</span><br><span class="line">21</span><br><span class="line">22</span><br><span class="line">23</span><br><span class="line">24</span><br><span class="line">25</span><br><span class="line">26</span><br><span class="line">27</span><br><span 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class="keyword">include</span> <span class="string">&lt;vector&gt;</span>                               <span class="comment">// 动态数组容器</span></span></span><br><span class="line"><span class="meta">#<span class="keyword">include</span> <span class="string">&lt;pcl/io/pcd_io.h&gt;</span>                     <span class="comment">// PCL 点云文件读写（PCD格式）</span></span></span><br><span class="line"><span class="meta">#<span class="keyword">include</span> <span class="string">&lt;pcl/point_types.h&gt;</span>                   <span class="comment">// PCL 内置点类型定义（如PointXYZ）</span></span></span><br><span class="line"><span class="meta">#<span class="keyword">include</span> <span class="string">&lt;pcl/visualization/cloud_viewer.h&gt;</span>    <span class="comment">// 点云可视化工具</span></span></span><br><span class="line"><span class="meta">#<span class="keyword">include</span> <span class="string">&lt;pcl/filters/passthrough.h&gt;</span>           <span class="comment">// 直通滤波器（PassThrough Filter）</span></span></span><br><span class="line"><span class="meta">#<span class="keyword">include</span> <span class="string">&lt;pcl/segmentation/min_cut_segmentation.h&gt;</span> <span class="comment">// 最小割分割算法</span></span></span><br><span class="line"><span class="meta">#<span class="keyword">include</span> <span class="string">&lt;pcl/console/print.h&gt;</span>                 <span class="comment">// PCL 控制台打印工具</span></span></span><br><span class="line"><span class="meta">#<span class="keyword">include</span> <span class="string">&lt;pcl/console/parse.h&gt;</span>                 <span class="comment">// 命令行参数解析工具</span></span></span><br><span class="line"><span class="meta">#<span class="keyword">include</span> <span class="string">&lt;pcl/console/time.h&gt;</span>                  <span class="comment">// 时间统计工具</span></span></span><br><span class="line"><span class="keyword">using</span> <span class="keyword">namespace</span> pcl::console;                  <span class="comment">// 使用PCL控制台命名空间，简化函数调用</span></span><br><span class="line"></span><br><span class="line"><span class="function"><span class="type">int</span> <span class="title">main</span> <span class="params">(<span class="type">int</span> argc, <span class="type">char</span>** argv)</span>               <span class="comment">// 主函数，支持命令行参数</span></span></span><br><span class="line"><span class="function"></span>&#123;</span><br><span class="line">	<span class="keyword">if</span>(argc &lt; <span class="number">2</span>)                                <span class="comment">// 如果参数少于2个（程序名 + 文件路径）</span></span><br><span class="line">	&#123;</span><br><span class="line">		std::cout &lt;&lt; <span class="string">&quot;.exe xx.pcd -bc 1 -fc 1.0 -nc 0 -cx 68.97 -cy -18.55 -cz 0.57 -s 0.25 -r 3.0433856 -non 14 -sw 0.5&quot;</span> &lt;&lt; std::endl;</span><br><span class="line">		<span class="comment">// 提示用户正确使用方式：可设置各种参数</span></span><br><span class="line">		<span class="keyword">return</span> <span class="number">0</span>;                               <span class="comment">// 参数不足则退出</span></span><br><span class="line">	&#125;</span><br><span class="line"></span><br><span class="line">	<span class="type">time_t</span> start, end, diff[<span class="number">5</span>], option;         <span class="comment">// 定义时间变量（用于性能分析）</span></span><br><span class="line">	start = <span class="built_in">time</span>(<span class="number">0</span>);                            <span class="comment">// 记录开始时间</span></span><br><span class="line"></span><br><span class="line">	<span class="type">int</span> NumberOfNeighbours = <span class="number">14</span>;                <span class="comment">// 默认邻域点数量（用于构建图）</span></span><br><span class="line">	<span class="type">bool</span> Bool_Cuting = <span class="literal">false</span>;                   <span class="comment">// 是否启用直通滤波（Z轴裁剪）</span></span><br><span class="line">	<span class="type">float</span> far_cuting = <span class="number">1</span>, near_cuting = <span class="number">0</span>;      <span class="comment">// Z轴滤波范围：[near_cuting, far_cuting]</span></span><br><span class="line">	<span class="type">float</span> C_x = <span class="number">0.071753</span>, C_y = <span class="number">-0.309913</span>, C_z = <span class="number">1.603000</span>; <span class="comment">// 前景点（种子点）坐标</span></span><br><span class="line">	<span class="type">float</span> Sigma = <span class="number">0.25</span>;                         <span class="comment">// 平滑成本的高斯权重参数σ</span></span><br><span class="line">	<span class="type">float</span> Radius = <span class="number">0.8</span>;                         <span class="comment">// 背景惩罚的距离阈值半径</span></span><br><span class="line">	<span class="type">float</span> SourceWeight = <span class="number">0.5</span>;                   <span class="comment">// 源点（前景）与汇点（背景）之间的连接权重</span></span><br><span class="line"></span><br><span class="line">	<span class="comment">// 创建指向PointXYZ类型点云的智能指针</span></span><br><span class="line">	pcl::PointCloud&lt;pcl::PointXYZ&gt;::<span class="function">Ptr <span class="title">cloud</span><span class="params">(<span class="keyword">new</span> pcl::PointCloud&lt;pcl::PointXYZ&gt;)</span></span>;</span><br><span class="line">	</span><br><span class="line">	<span class="comment">// 加载PCD文件到点云对象，失败返回-1</span></span><br><span class="line">	<span class="keyword">if</span> (pcl::io::<span class="built_in">loadPCDFile</span>&lt;pcl::PointXYZ&gt;(argv[<span class="number">1</span>], *cloud) == <span class="number">-1</span>)</span><br><span class="line">	&#123;</span><br><span class="line">		std::cout &lt;&lt; <span class="string">&quot;Cloud reading failed.&quot;</span> &lt;&lt; std::endl;</span><br><span class="line">		<span class="keyword">return</span> (<span class="number">-1</span>);</span><br><span class="line">	&#125;</span><br><span class="line"></span><br><span class="line">	<span class="comment">// 解析命令行参数，覆盖默认值</span></span><br><span class="line">	<span class="built_in">parse_argument</span>(argc, argv, <span class="string">&quot;-bc&quot;</span>, Bool_Cuting);       <span class="comment">// 是否开启直通滤波</span></span><br><span class="line">	<span class="built_in">parse_argument</span>(argc, argv, <span class="string">&quot;-fc&quot;</span>, far_cuting);        <span class="comment">// 远裁剪面（Z最大值）</span></span><br><span class="line">	<span class="built_in">parse_argument</span>(argc, argv, <span class="string">&quot;-nc&quot;</span>, near_cuting);       <span class="comment">// 近裁剪面（Z最小值）</span></span><br><span class="line"></span><br><span class="line">	<span class="built_in">parse_argument</span>(argc, argv, <span class="string">&quot;-cx&quot;</span>, C_x);               <span class="comment">// 前景点X坐标</span></span><br><span class="line">	<span class="built_in">parse_argument</span>(argc, argv, <span class="string">&quot;-cy&quot;</span>, C_y);               <span class="comment">// 前景点Y坐标</span></span><br><span class="line">	<span class="built_in">parse_argument</span>(argc, argv, <span class="string">&quot;-cz&quot;</span>, C_z);               <span class="comment">// 前景点Z坐标</span></span><br><span class="line"></span><br><span class="line">	<span class="built_in">parse_argument</span>(argc, argv, <span class="string">&quot;-s&quot;</span>, Sigma);              <span class="comment">// Sigma值（边权重中的平滑项）</span></span><br><span class="line">	<span class="built_in">parse_argument</span>(argc, argv, <span class="string">&quot;-r&quot;</span>, Radius);             <span class="comment">// Radius（背景惩罚距离）</span></span><br><span class="line">	<span class="built_in">parse_argument</span>(argc, argv, <span class="string">&quot;-non&quot;</span>, NumberOfNeighbours); <span class="comment">// 邻居数量</span></span><br><span class="line">	<span class="built_in">parse_argument</span>(argc, argv, <span class="string">&quot;-sw&quot;</span>, SourceWeight);      <span class="comment">// Source权重（前景连接强度）</span></span><br><span class="line"></span><br><span class="line">	<span class="comment">// 创建索引指针，用于保存滤波后的点索引</span></span><br><span class="line">	<span class="function">pcl::IndicesPtr <span class="title">indices</span><span class="params">(<span class="keyword">new</span> std::vector&lt;<span class="type">int</span>&gt;)</span></span>;</span><br><span class="line"></span><br><span class="line">	<span class="keyword">if</span> (Bool_Cuting) <span class="comment">// 如果启用直通滤波</span></span><br><span class="line">	&#123;</span><br><span class="line">		pcl::PassThrough&lt;pcl::PointXYZ&gt; pass;             <span class="comment">// 创建直通滤波器对象</span></span><br><span class="line">		pass.<span class="built_in">setInputCloud</span>(cloud);                        <span class="comment">// 设置输入点云</span></span><br><span class="line">		pass.<span class="built_in">setFilterFieldName</span>(<span class="string">&quot;z&quot;</span>);                     <span class="comment">// 指定按Z轴过滤</span></span><br><span class="line">		pass.<span class="built_in">setFilterLimits</span>(near_cuting, far_cuting);    <span class="comment">// 设置Z轴范围</span></span><br><span class="line">		pass.<span class="built_in">filter</span>(*indices);                            <span class="comment">// 执行滤波，结果存入indices</span></span><br><span class="line">	&#125;</span><br><span class="line"></span><br><span class="line">	<span class="comment">// 创建最小割分割对象（基于图割的分割方法）</span></span><br><span class="line">	pcl::MinCutSegmentation&lt;pcl::PointXYZ&gt; seg;</span><br><span class="line">	seg.<span class="built_in">setInputCloud</span>(cloud);                             <span class="comment">// 设置输入点云</span></span><br><span class="line"></span><br><span class="line">	<span class="keyword">if</span> (Bool_Cuting)</span><br><span class="line">		seg.<span class="built_in">setIndices</span>(indices);                          <span class="comment">// 若有滤波，则使用滤波后的索引</span></span><br><span class="line"></span><br><span class="line">	<span class="comment">// 创建前景点云（仅包含一个种子点）</span></span><br><span class="line">	pcl::PointCloud&lt;pcl::PointXYZ&gt;::<span class="function">Ptr <span class="title">foreground_points</span><span class="params">(<span class="keyword">new</span> pcl::PointCloud&lt;pcl::PointXYZ&gt;())</span></span>;</span><br><span class="line">	pcl::PointXYZ point;</span><br><span class="line">	point.x = C_x;</span><br><span class="line">	point.y = C_y;</span><br><span class="line">	point.z = C_z;</span><br><span class="line">	foreground_points-&gt;points.<span class="built_in">push_back</span>(point);           <span class="comment">// 添加用户指定的中心点作为前景种子</span></span><br><span class="line"></span><br><span class="line">	seg.<span class="built_in">setForegroundPoints</span>(foreground_points);           <span class="comment">// 设置前景点（引导分割方向）</span></span><br><span class="line"></span><br><span class="line">	seg.<span class="built_in">setSigma</span>(Sigma);                                  <span class="comment">// 设置边权重中的平滑系数σ</span></span><br><span class="line">	seg.<span class="built_in">setRadius</span>(Radius);                                <span class="comment">// 设置背景惩罚半径：距离该半径外视为背景</span></span><br><span class="line">	seg.<span class="built_in">setNumberOfNeighbours</span>(NumberOfNeighbours);        <span class="comment">// 设置每个点的邻接点数量（影响图结构）</span></span><br><span class="line">	seg.<span class="built_in">setSourceWeight</span>(SourceWeight);                    <span class="comment">// 设置源点（前景）与所有点连接的权重</span></span><br><span class="line"></span><br><span class="line">	std::vector&lt;pcl::PointIndices&gt; clusters;              <span class="comment">// 存储分割结果（点索引组）</span></span><br><span class="line">	seg.<span class="built_in">extract</span>(clusters);                                <span class="comment">// 执行最小割分割算法</span></span><br><span class="line"></span><br><span class="line">	std::cout &lt;&lt; <span class="string">&quot;Maximum flow is &quot;</span> &lt;&lt; seg.<span class="built_in">getMaxFlow</span>() &lt;&lt; std::endl; <span class="comment">// 输出最大流值（图割结果）</span></span><br><span class="line"></span><br><span class="line">	<span class="comment">// 获取着色后的点云：前景为红色，背景为白色</span></span><br><span class="line">	pcl::PointCloud&lt;pcl::PointXYZRGB&gt;::Ptr colored_cloud = seg.<span class="built_in">getColoredCloud</span>();</span><br><span class="line"></span><br><span class="line">	<span class="comment">// 创建可视化窗口</span></span><br><span class="line">	pcl::<span class="function">visualization::PCLVisualizer <span class="title">viewer</span><span class="params">(<span class="string">&quot;based on min cut segmentation&quot;</span>)</span></span>;</span><br><span class="line">	viewer.<span class="built_in">addPointCloud</span>(colored_cloud);                  <span class="comment">// 显示分割结果</span></span><br><span class="line">	viewer.<span class="built_in">addSphere</span>(point, Radius, <span class="number">122</span>, <span class="number">122</span>, <span class="number">0</span>, <span class="string">&quot;sphere&quot;</span>); <span class="comment">// 添加一个半透明球体表示背景惩罚范围</span></span><br><span class="line">	viewer.<span class="built_in">setShapeRenderingProperties</span>(pcl::visualization::PCL_VISUALIZER_OPACITY, <span class="number">0.2</span>, <span class="string">&quot;sphere&quot;</span>); <span class="comment">// 设置透明度</span></span><br><span class="line"></span><br><span class="line">	<span class="keyword">while</span> (!viewer.<span class="built_in">wasStopped</span>())                          <span class="comment">// 循环刷新视图直到关闭</span></span><br><span class="line">	&#123;</span><br><span class="line">		viewer.<span class="built_in">spin</span>();</span><br><span class="line">	&#125;</span><br><span class="line"></span><br><span class="line">	<span class="keyword">return</span> <span class="number">0</span>;</span><br><span class="line">&#125;</span><br></pre></td></tr></table></figure>

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</article><div class="post-copyright"><div class="post-copyright__author"><span class="post-copyright-meta"><i class="fas fa-circle-user fa-fw"></i>文章作者: </span><span class="post-copyright-info"><a href="https://ckyfi9zero.github.io">Fi9zero</a></span></div><div class="post-copyright__type"><span class="post-copyright-meta"><i class="fas fa-square-arrow-up-right fa-fw"></i>文章链接: </span><span class="post-copyright-info"><a href="https://ckyfi9zero.github.io/2025/08/05/2025-08-05-%E5%9F%BA%E4%BA%8E%E6%9C%80%E5%B0%8F%E5%89%B2%E7%9A%84%E5%88%86%E5%89%B2/">https://ckyfi9zero.github.io/2025/08/05/2025-08-05-%E5%9F%BA%E4%BA%8E%E6%9C%80%E5%B0%8F%E5%89%B2%E7%9A%84%E5%88%86%E5%89%B2/</a></span></div><div class="post-copyright__notice"><span class="post-copyright-meta"><i class="fas fa-circle-exclamation fa-fw"></i>版权声明: </span><span class="post-copyright-info">本博客所有文章除特别声明外，均采用 <a href="https://creativecommons.org/licenses/by-nc-sa/4.0/" target="_blank">CC BY-NC-SA 4.0</a> 许可协议。转载请注明来源 <a 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class="toc-link" href="#PCL-%E6%9C%80%E5%B0%8F%E5%89%B2%E5%88%86%E5%89%B2%EF%BC%88Min-Cut-Segmentation%EF%BC%89"><span class="toc-number">1.</span> <span class="toc-text">PCL 最小割分割（Min-Cut Segmentation）</span></a><ol class="toc-child"><li class="toc-item toc-level-2"><a class="toc-link" href="#%E6%A0%B8%E5%BF%83%E5%8E%9F%E7%90%86"><span class="toc-number">1.1.</span> <span class="toc-text">核心原理</span></a></li><li class="toc-item toc-level-2"><a class="toc-link" href="#%E5%85%B3%E9%94%AE%E5%8F%82%E6%95%B0%E8%AF%B4%E6%98%8E"><span class="toc-number">1.2.</span> <span class="toc-text">关键参数说明</span></a></li><li class="toc-item toc-level-2"><a class="toc-link" href="#%E5%91%BD%E4%BB%A4%E8%A1%8C%E4%BD%BF%E7%94%A8%E6%96%B9%E5%BC%8F"><span class="toc-number">1.3.</span> <span class="toc-text">命令行使用方式</span></a></li><li class="toc-item toc-level-2"><a class="toc-link" href="#%E5%8F%AF%E8%A7%86%E5%8C%96%E6%8A%80%E5%B7%A7"><span class="toc-number">1.4.</span> <span class="toc-text">可视化技巧</span></a></li><li class="toc-item toc-level-2"><a class="toc-link" href="#%E5%B8%B8%E8%A7%81%E9%97%AE%E9%A2%98%E4%B8%8E%E4%BC%98%E5%8C%96%E5%BB%BA%E8%AE%AE"><span class="toc-number">1.5.</span> <span class="toc-text">常见问题与优化建议</span></a></li><li class="toc-item toc-level-2"><a class="toc-link" href="#%E5%85%B8%E5%9E%8B%E5%BA%94%E7%94%A8%E5%9C%BA%E6%99%AF"><span class="toc-number">1.6.</span> <span class="toc-text">典型应用场景</span></a></li><li class="toc-item toc-level-2"><a class="toc-link" href="#%E4%BB%A3%E7%A0%81%E5%AE%9E%E7%8E%B0"><span class="toc-number">1.7.</span> <span class="toc-text">代码实现</span></a></li></ol></li></ol></div></div><div class="card-widget card-recent-post"><div class="item-headline"><i class="fas fa-history"></i><span>最新文章</span></div><div class="aside-list"><div class="aside-list-item no-cover"><div class="content"><a class="title" href="/2025/10/05/2025-10-05-lio_sam/" title="lio_sam">lio_sam</a><time datetime="2025-10-05T02:43:51.000Z" 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